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Record W1965940645 · doi:10.1115/imece2013-65406

Mechanotransduction in Corneal Epithelial Cells

2013· article· en· W1965940645 on OpenAlexaff
Sara Molladavoodi, John B. Medley, Maud Gorbet, Hyock‐Ju Kwon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCorneaKeratoconusMechanotransductionCell biologyCorneal epitheliumAdhesionActinMaterials scienceIntegrinBiophysicsEpitheliumChemistryCellBiologyOphthalmologyComposite materialMedicineBiochemistry

Abstract

fetched live from OpenAlex

Mechanical properties of the cornea can be affected by diseases such as keratoconus. In keratoconus, a decrease in both thickness and rigidity of the cornea is observed. It is currently not clear whether and how changes in mechanical properties of the cornea are associated with corneal epithelial cell behavior. In the present study, polyacrylamide (PAA) gels with different elastic moduli have been prepared and human corneal epithelial cells (HCECs) have been cultured on them. To investigate the effect that changes in elastic modulus may have on adhesion and migration of corneal epithelial cells, actin filament organization and expression of adhesion molecules were characterized. It was found that HCECs actin filament organization improves with increasing substrate stiffness and integrin α3 expression significantly increases on more compliant substrates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.224
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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